Paper Title :Speech Emotion Recognition Using Iterative Clustering Technique
Author :R.anila, Dr. A. Revathy
Article Citation :R.anila ,Dr. A. Revathy ,
(2015 ) " Speech Emotion Recognition Using Iterative Clustering Technique " ,
International Journal of Advance Computational Engineering and Networking (IJACEN) ,
pp. 126-129,
Volume-3, Issue-6
Abstract : This paper proposes a method to recognize the emotion present in the speech signal using Iterative clustering
technique. We propose Mel Frequency Perceptual Linear Predictive Cepstrum (MFPLPC) as a feature for recognizing the
emotions. This feature is extracted from the speech and the clustering models are generated for each emotion. For the
Speaker Independent classification technique, pre- processing is done on test speeches and features are extracted. In K-
means clustering algorithm, the classification is based on the minimum distance between each test vector and centroid of
clusters. Mean of the minimum distances for each speech is found out. The test speech belongs to the model which has
minimum of averages corresponds to particular emotion. We obtained better recognition rate by using MFPLPC feature for a
cluster size 1024. The results are obtained for SAVEE database using data of seven emotional states such as anger, disgust,
fear, happy, sad, surprise and neutral.
KeyWords- Emotion recognition (ER), Mel Frequency Perceptual Linear Predictive Cepstrum (MFPLPC), Vector
Quantization (VQ).
Type : Research paper
Published : Volume-3, Issue-6
DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-2371
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Copyright: © Institute of Research and Journals
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Published on 2015-06-17 |
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